Careers

Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer’s doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! Amazon STEP Science and Tech is seeking Applied (or Research) Scientists. As a key member of the central Research Science Team of logistic operations, these persons will be responsible for designing algorithmic solutions based on data and mathematics for optimizing the end-to-end Amazon supply chain network. The job is opened in the EU Headquarters in Luxembourg (alternatively: Barcelona, Berlin or London), designed to maximize interaction with the team and stakeholders. Basic qualifications * PhD in Operations Research, Machine Learning, Statistics, Applied Mathematics, Computer Science or other field related to algorithms and data (or equivalent experience). * Excellent written and verbal communication skills. * Experience with some programming language (Java/python/C++) * Research experience in one or more: *Combinatorial optimization problems (e.g., scheduling, vehicle routing, facility location). *Continuous optimization problems (e.g., linear programming, convex programming, non-convex programming). Preferred qualifications * Experience from working in a fast-paced applied research environment. * Ability to handle ambiguity. * Top tier publications pertinent to the field of study. Key job responsibilities Solve complex optimization and machine learning problems using scalable algorithmic techniques. Design and develop efficient research prototypes that address real-world problems in the massive logistics network of Amazon. Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making. Communicate to leadership results from business analysis, strategies and tactics. A day in the life You will be brainstorming algorithmic approaches with team-mates to solve challenging problems for Amazon logistics operations. You will be developing and testing prototype solutions with above algorithmic techniques. You will be scavenging information from the sea of Amazon data to improve these solutions. You will be meeting with other scientists, engineers, stakeholders and customers to enhance the solutions and get them adopted. About the team The Science and Tech (SnT) team of EU STEP is looking for candidates who are looking to impact the world with their mathematical and data-driven skills. We are the End-to-End Supply Chain optimizers. As the core research team, we grow Amazon's logistics business to support decision making in an increasingly complex ecosystem of a data-driven supply chain and e-commerce giant. Our mathematical algorithms provide confidence in leadership to invest in programs of several hundreds millions euros every year. Above all, we are having fun solving real-world problems, in real-world speed, while failing & learning along the way. We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms. We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making. We like to learn new techniques to surprise business stakeholders by making possible what they cannot anticipate. For this reason, we work closely with Amazon scholars and experts from Academic institutions. We code our prototypes to be production-ready We prefer provably optimal solutions than heuristics, though we settle for heuristics when performance dictates it. Overall, we appreciate the value of correct modeling.

Lead the development of cutting-edge AI models to power Amazon's eCommerce ontology - the authoritative source of product knowledge driving exceptional customer experiences. Applied Scientists in this role solve problems related to product classification, attribute extraction, ontology modeling, data integration and enrichment, and scalable knowledge services. It's challenging due to the vast scale, heterogeneous data sources, and evolving domains, but exciting for pushing boundaries in ML, NLP, and knowledge representation research. If you're passionate about driving innovation at scale, we want to hear from you! Key job responsibilities - Lead the research and development of novel AI solutions to enrich and curate Amazon's product ontology (Product Knowledge) at scale - Develop scalable data processing pipelines and architectures to ingest, transform, and enrich product data from various sources (seller listings, customer reviews, etc.) - Collaborate with engineers to design and implement robust services - Work closely with product managers, stakeholders, and subject matter experts to identify opportunities for innovation and drive the roadmap for Product Knowledge - Mentor and upskill junior scientists and engineers, fostering a culture of continuous learning and knowledge sharing - Communicate complex technical concepts and research findings effectively to diverse audiences, including leadership, cross-functional teams, and the wider scientific community - Stay up-to-date with the latest advancements in machine learning, natural language processing, knowledge representation, and related fields, and identify opportunities to apply them to Product Knowledge A day in the life The Amazon product ontology is a structured knowledge base representing product types, attributes, classes, and relationships. It standardizes product data, enabling enhanced customer experiences through improved search and recommendations, streamlined selling processes, and internal data enrichment across Amazon's eCommerce ecosystem. You will work with following stakeholders: - Product Managers represent customer experiences and selling partner experiences - Category Leaders (e.g., apparel, electronics) provide domain knowledge and guidance as subject matter experts - Engineers build and maintain data pipelines and services in production - Ontologists design data models and define guidelines - Other Applied Scientists collaborate on research and innovation About the team The Product Knowledge team at Amazon is dedicated to creating the industry-standard eCommerce product and services ontology. Our diverse team of applied scientists, engineers, ontologists and subject matter experts build a comprehensive ontology enabling exceptional customer and selling partner experiences through high-quality, contextual product knowledge at scale.

Do you want to create the greatest-possible worldwide impact in Robotics? Amazon has the world's most exciting treasure trove of robotics challenges. At Amazon Robotics we build high-performance, real-time robotic systems that can perceive, learn, and act intelligently alongside humans—at Amazon scale. Amazon Robotics invents and scales AI systems for robotics in fulfillment. Our mission is to enable robots to interact safely, efficiently, and fluently high density real-world fulfillment centers. Our AI solutions enable robots to learn from their own experiences, from each other, and from humans to build intelligence that feeds itself. We hire and develop subject matter experts in AI with a focus on computer vision, deep learning, semi-supervised and unsupervised learning. We target high-impact algorithmic unlocks in areas such as scene and activity comprehension, large scale generative models, closed-loop control, robotic grasping and manipulation—all of which have high-value impact for our current and future fulfillment networks. We are seeking passionate, hands-on, experienced and seasoned Senior Applied Scientist who will be deep in code and algorithms; who are technically strong in building scalable computer vision machine learning systems across item understanding, pose estimation, class imbalanced classifiers, identification and segmentation. As a Senior Applied Scientist, you will contribute to the research and development of advanced robotic systems; your work along with other top-notch scientists and engineers will deliver the world's most scalable and robust robotic systems. You will drive ideas to products using paradigms such as deep learning, semi supervised learning and dynamic learning. As a Senior Applied Scientist, you will also help lead and mentor our team of applied scientists and engineers. You will take on complex customer problems, distill customer requirements, and then deliver solutions that either leverage existing academic and industrial research or utilize your own out-of-the-box but pragmatic thinking. In addition to coming up with novel solutions and prototypes, you will directly contribute to implementation while you lead. A successful candidate has excellent technical depth, scientific vision, project management skills, great communication skills, and a drive to achieve results in a unified team environment. You should enjoy the process of solving real-world problems that, quite frankly, haven’t been solved at scale anywhere before. Along the way, we guarantee you’ll get opportunities to be a bold disruptor, prolific innovator, and a reputed problem solver—someone who truly enables AI and robotics to significantly impact the lives of millions of consumers. Key job responsibilities Architect, design, and implement Machine Learning models for vision systems on robotic platforms Optimize, deploy, and support at scale ML models on the edge. Influence the team's strategy and contribute to long-term vision and roadmap. Work with stakeholders across , science, and operations teams to iterate on design and implementation. Maintain high standards by participating in reviews, designing for fault tolerance and operational excellence, and creating mechanisms for continuous improvement. Prototype and test concepts or features, both through simulation and emulators and with live robotic equipment Work directly with customers and partners to test prototypes and incorporate feedback Mentor other engineer team members. A day in the life Amazon offers a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team https://www.amazon.science/latest-news/how-amazon-robotics-researchers-are-solving-a-beautiful-problem

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Detail Page Discovery Experiences team is chartered with inventing and building engaging product recommendation experiences in Amazon Product Detail Pages. We push the innovation frontiers for our hundreds of millions of customers WW to aid product discovery while helping shoppers to find relevant products easily. Our team is building differentiated recommendations and utilizing cutting-edge machine learning techniques in the domain of natural language processing (NLP) and Transformer, deep learning, reinforcement learning, and Generative AI to provide delightful shopping experiences and deliver significant impact for the business. We are looking for an Applied Scientist who can delight our customers by continually learning and inventing. Our ideal candidate is an experienced Applied Scientist who has a track-record of performing deep analysis and is passionate about applying advanced ML and statistical techniques to solve real-world, ambiguous and complex challenges to optimize and improve the product performance, and who is motivated to achieve results in a fast-paced environment. The position offers an exceptional opportunity to grow your technical and non-technical skills and make a real difference to the Amazon Advertising business. As an Applied Scientist in the Blended Widgets team, you will: * Conduct hands-on data analysis, and run regular A/B experiments, gather data, perform statistical analysis and deep dive, and communicate the impact to senior management * Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgment * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Collaborate with software engineering teams to integrate successful experimental results into large-scale, highly complex Amazon production systems * Promote the culture of experimentation and applied science at Amazon Team video https://youtu.be/zD_6Lzw8raE We are also open to consider the candidate in New York, or Seattle.

The Measurement, Ad Tech, and Data Science (MADS) team at Amazon Ads is at the forefront of developing cutting-edge solutions that help our tens of millions of advertisers understand the value of their ad spend while prioritizing customer privacy and measurement quality. We develop cutting-edge deterministic algorithms, machine learning models, causal models, and statistical approaches to empower advertisers with insights on the effectiveness of their ads in guiding customers from awareness to purchases. Our insights help advertisers build full-funnel advertising strategies. We maximize the information we extract from incomplete traffic signals and alternative sources to capture the impact of their ad spending for both Amazon recognized and anonymous traffic. Our vision is to lead the industry in extracting and combining information from several sources to enable advertisers to optimize their return on their ad spend. As an Applied Scientist on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE Key job responsibilities * Lead the development of ad measurement models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies. * Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions. * Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop cutting-edge models that measure the impact of ad spend across multiple platforms and timescales. * Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization. * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Foster collaborations between scientists to move faster, with broader impact. * Regularly engage with the broader scientific community with presentations, publications, and patents. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Team video https://advertising.amazon.com/help/G4LNN5YWHP6SM9TJ

The Advertising Incrementality Measurement (AIM) team is looking for an Applied Scientist II with experience in causal inference, experimentation, and ML development to help us expand our causal modeling solutions for understanding advertising effectiveness. Our work is foundational to providing customer-facing experimentation tools, furthering internal research & development, and building out Amazon's new Multi-Touch Attribution (MTA) measurement offerings. Incrementality measurement is a lynchpin for the next generation of Amazon Advertising measurement solutions and this role will play a key role in the release and expansion of these offerings. Key job responsibilities * Partner with economists and senior team members to drive science improvements and implement technical solutions at the state-of-the-art of machine learning and econometrics * Partner with engineering and other science collaborators to design, implement, prototype, deploy, and maintain large-scale causal ML models. * Carry out in-depth research and analysis exploring advertising-related data sets, including large sets of real-world experimental data, to understand advertiser behavior, highlight model improvement opportunities, and understand shortcomings and limitations. * Define data quality standards for understanding typical behavior, capturing outliers, and detecting model performance issues. * Work with product stakeholders to help improve our ability to provide quality measurement of advertising effectiveness for our customers. About the team AIM is a cross disciplinary team of engineers, product managers, economists, data scientists, and applied scientists with a charter to build scientifically-rigorous causal inference methodologies at scale. Our job is to help customers cut through the noise of the modern advertising landscape and understand what actions, behaviors, and strategies actually have a real, measurable impact on key outcomes. The data we produce becomes the effective ground truth for advertisers and partners making decisions affecting $10s to $100s of millions in advertising spend.

SCOT's Regional team in Japan is seeking a passionate and driven Senior Applied Scientist to lead localization efforts around substitution science with a primary focus on improving customer experience in a sustainable manner. This would include adapting WW datasets incorporating country specific requirements (e.g. Japanese language, translations) to model basket awareness and speed sensitivity of large cohorts of products. You will work with product managers, BIEs, and business teams to understand the business problems and requirements, evaluate existing science models and distill that understanding to crisply define durable yet frugal improvements to address local challenges. You will tackle complex technical challenges that require extensible solutions while collaborating with multiple teams across EU, IN and Emerging Countries to assess overall opportunity for customers and design experiments to benchmark/baseline impact. As a Senior Applied Scientist, you will create and implement sophisticated machine learning solutions while creating technical strategies with minimal supervision. The ideal candidate possesses extensive knowledge and hands-on experience, particularly in areas such as deep learning systems, computer vision, or natural language processing. You should demonstrate superior analytical and quantitative skills, with proven experience in data collection, model building, testing and validation. Proficiency in programming languages like Python, R, or Matlab, along with expertise in machine learning frameworks such as PyTorch, TensorFlow, etc. is essential. We value professionals who can earn trust through strong communication with stakeholders, understand business requirements, and deliver solutions that address specific needs. You should have the ability to think strategically and connect scientific solutions to create significant impact for customers. The role requires mentoring junior colleagues, contributing to the career development of team members, and fostering a collaborative environment. Success in this position demands a self-driven desire to learn new domains, strong ownership mentality, and the ability to deliver results while maintaining high standards. Experience with AWS or other cloud technologies and distributed systems would be advantageous. Key job responsibilities - Design and implement novel scientific solutions while working backwards from customer needs and product requirements to deliver measurable business impact - Lead complex cross-functional projects and ensure high-quality solutions by collaborating with solutions architects, developers, product managers, and senior leadership - Create technical strategies and roadmaps for forward-looking research, communicating them effectively to senior leadership - Develop and implement scalable algorithms and solutions that are extensible for future needs - Conduct hands-on experimentation and deliver results in the form of new products while maintaining strong analytical and quantitative standards - Research and benchmark technology solutions against competing systems in the industry - Exert technical influence across multiple teams by sharing deep knowledge and experience to increase productivity and effectiveness - Communicate technical concepts and solutions appropriately for both technical and non-technical audiences while earning trust of business decision-makers About the team Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment working with smart & passionate team members. (Learn more about SCOT: http://bit.ly/amazon-scot)

Amazon's Pricing & Promotions Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon and Third Party Seller products worldwide. We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing and Promotions Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon. This role requires an individual with exceptional machine learning and reinforcement learning modeling expertise, excellent cross-functional collaboration skills, outstanding business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. Key job responsibilities - See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques - Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale - Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems - Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. - Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems. A day in the life We are hiring an applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through: * invent and deliver price optimization, simulation, and competitiveness tools for Sellers. * shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs. * Promotion optimization initiatives exploring CX, discount amount, and cross-product optimization opportunities. * Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods) Price is a highly relevant input into many partner-team architectures, and is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication. About the team About the team: the Pricing Discovery and Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.

Amazon One Medical is hiring a Actuarial Manager Analyst. Actuarial rigor is one of the keys to our success. This candidate will responsible primarily for several critical workstreams which include analysis of Medicare Advantage and Accountable Care Organization data, design and implement an actuarially sound monthly reserving process for Total Medical Expense (TME) estimation, and lead continuous evaluation of TME performance compared to plan expectations. Key job responsibilities -Analysis of Medicare Advantage and Accountable Care Organization data primarily -Medical economics reporting and ad-hoc analysis relating to cost of care management -Medicare Risk score projections and premium estimation -Design and implement an actuarially sound monthly reserving process for Total Medical Expense (TME) estimation -Lead continuous evaluation of TME performance compared to plan expectations -Coordinate with the finance team on future TME projections that are refreshed monthly and provided quarterly for forecasting and planning -Support month end financial and accounting processes for relevant actuarial estimates. -Value based care contracting support and ongoing financial and risk analysis. -Support ongoing actuarial support for outside auditor review of financial estimates and results. -Design studies to monitor the suitability of the completion factor estimates. -Lead continuous evaluation of risk based funding and scoring performance compared to plan expectations. -Complete the evaluation of stop-loss coverage and manage third party vendors -Analyze and develop new to market assessments and modeling which includes future Medicare geographic expansion and enhancements / changes to other market segments (Commercial potentially)

Are you passionate about automation, optimization, knowledge extraction, and artificial intelligence through the use of Machine Learning, Computer Vision, Optimization, Natural Language Processing, and Recommender systems? We have a team of experienced scientists with a critical business mission making revolutionary leaps forward in these spaces. On this team you will work with large multimodal datasets to build generative and discriminative models for optimizing large-scale manufacturing and fulfillment processes, analyze and model customer reading behavior to measure engagement and detect risks, and build AI-based systems for helping indie authors make their businesses successful. This will involve combining methods from several science domains with domain knowledge across multiple businesses into sophisticated ML workflows. Our team has mature areas and green-field opportunities. We offer scientific autonomy, value end-to-end ownership, and have a strong customer-focused culture. As a Research Scientist at Amazon, you will connect with world leaders in your field working on similar problems. You will be working with large distributed systems of data and providing technical leadership to the product managers, teams, and organizations building machine learning solutions. You will be tackling Machine Learning challenges in Supervised, Unsupervised, and Semi-supervised Learning; utilizing modern methods such as deep learning and classical methods from statistical learning theory, detection, estimation. Research Scientists are specialists with the deep expertise to drive the scientific vision for our products. They are externally aware of the state-of-the-art in their respective field of expertise and are constantly focused on advancing that state-of-the-art for improving Amazon’s products and services. Come join us as we revolutionize the book industry and deliver an amazing experience to our Kindle authors and readers. Key job responsibilities Great candidates for this position will be experts in the areas of data science, machine learning, computer vision, optimization, NLP, or statistics. You will have hands-on experience with multiple science initiatives as well as be able to balance technical leadership with strong business judgment to make the right decisions about technology, models and methodological choices. You will strive for simplicity, and demonstrate significant creativity and high judgment. About the team Kindle Direct Publishing (KDP) and Print On Demand (POD) have empowered a new wave of self-motivated creators, tearing down barriers that once blocked writers from reaching readers. Our team builds rich applications and systems that empower anyone to realize their dream of becoming a published author. We strive to provide an experience that is powerful, yet simple to use and accessible to all. We focus on building systems that enable authors to design high quality digital and print books, reaching readers all around the world. This role will help ensure we maintain the trust of both our Authors and Readers by ensuring all books published to Amazon meet our standards.